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Sonic Xplorer: A Machine Learning Approach for Parametric Exploration of Sound

Electronic Visualisation and the Arts (EVA 2017) (EVA)

Electronic Visualisation and the Arts

11 – 13 July 2017

Sound synthesis, Multiparametric control, Artificial neural networks, Sound timbre, Semantic descriptors

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      Abstract

      This paper presents Sonic Xplorer an interfaces that uses timbre adjectives for multiparametric control sound synthesis. The interface utilises an artificial neural network to create a personalised interface. Users can manipulate a large number of sound synthesis parameters without the need to learn or use the synthesiser’s complex interface by utilising programed sounds by expert users. Sonic Xplorer learns a correlation based on users’ ratings between timbre adjectives and the acoustic descriptors. Timbre adjectives are then used to describe the acoustic qualities of the desired sound. This paper discusses in detail the approach that has been followed to develop the system and the mapping and strategies users employed when using the interface in order to discover new sounds.

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      Most cited references 13

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      The Importance of Parameter Mapping in Electronic Instrument Design

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        Exploring violin sound quality: Investigating English timbre descriptors and correlating resynthesized acoustical modifications with perceptual properties

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            Author and article information

            Affiliations
            Centre for Interaction Design

            Edinburgh Napier University

            10 Colinton Road, EH10 5DT

            Scotland
            Contributors
            Conference
            July 2017
            July 2017
            : 144-149
            10.14236/ewic/EVA2017.34
            © Tsiros. Published by BCS Learning and Development Ltd. Proceedings of EVA London 2017, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Electronic Visualisation and the Arts (EVA 2017)
            EVA
            London, UK
            11 – 13 July 2017
            Electronic Workshops in Computing (eWiC)
            Electronic Visualisation and the Arts
            Product
            Product Information: 1477-9358 BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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